Update app.py

app.py

@@ -1,6 +1,6 @@
-# import streamlit as st
-# from transformers import AutoTokenizer, AutoModelForTokenClassification
-# from transformers import pipeline
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+from transformers import pipeline
 
 # tokenizer = AutoTokenizer.from_pretrained("Davlan/bert-base-multilingual-cased-ner-hrl")
 # model = AutoModelForTokenClassification.from_pretrained("Davlan/bert-base-multilingual-cased-ner-hrl")
@@ -11,7 +11,6 @@
 # if example:
 #     ner_results = nlp(example)
 #     st.json(ner_results)
-from transformers import pipeline
 
 # Load pre-trained NER model
 ner = pipeline('ner', model='has-abi/distilBERT-finetuned-resumes-sections', tokenizer='bert-base-cased')